## No Dig for Victory

3Dimensional Greenhouse

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# Category: systems

## No Dig for Victory

## The Palm Arms

## Mimicking the Geometry

## Palm Wine

## Alternative Fuel

## Future Proposal

## Transcendental Staircase

## Plants, Math, Spirals, & the Value of the Golden Ratio

# 1.0 Phyllotaxis Spirals

### 1.1 Rational Numbers

*Phyllotaxis Study: 180° (see corn leaves), 90° (see mint leaves), and 72° (see gentiana petals)*
*Phyllotaxis Study – 1,000 Seed Spread: 45***°**, 36**°**, and 20**°**
*Phyllotaxis Study – 1,000 Seed Spread: 8***°**, 5**°**, and 2**°**
### 1.2 Irrational Numbers

*Phyllotaxis Growth Study: Pi, Square Root of 2, and Euler’s Number*
*Phyllotaxis Study – 1,000 Seed Spread: Pi, Square Root of 2, and Euler’s Number*
### 1.3 Quantifiable irrationality

*Phyllotaxis Voronoi Diagram – Proximity to Closest Neighbour: Pi*
*Phyllotaxis Voronoi Diagram – Proximity to Closest Neighbour: Square Root of 2, and Euler’s Number*
### 1.4 Phi

*Phyllotaxis Study: The Golden Ratio*
*Phyllotaxis Voronoi Diagram – Proximity to Closest Neighbour – 1,000 Seed Spread: The Golden Ratio*
### 1.5 The Metallic Means & Other Constants

*Phyllotaxis Voronoi /Proximity Study: Various Known Mathematical Constants*
### 1.6 Why Spirals?

## The Nature of Gridshell Form Finding

### Foreword

# 7.0 Introduction to Shells

### 7.1 – Single Curved Surfaces

Uniclastic: Barrel Vault (Cylindrical paraboloid)

Uniclastic: Conoid (Conical paraboloid)### 7.2 – Double Curved Surfaces

Synclastic: Dome (Elliptic paraboloid)
Anticlastic: Saddle (Hyperbolic paraboloid)
Kellogg’s potato and wheat-based stackable snack
Structural Behaviour of Basic Shells [Source: IL 10 – Institute for Lightweight Structures and Conceptual Design]
### 7.3 – Translation vs Revolution

Hyperbolic Paraboloid: Straight line sweep variation
**Ruled Surface & Surface of Revolution (Circular Hyperboloid)**
Hyperboloid Generation [Source:Wikipedia]
# 8.0 Geodesic Curves

Conic Plank Lines (Source: *The Geometry of Bending*)
### 8.1 – Basic Grid Setup

Basic geodesic curves on a plane
Initial set of curves
Addition of secondary set of curves
Grid with independent sets
### 8.2 – Basic Gridshells

Uniclastic: Barrel Vault Geodesic Gridshell
Uniclastic: Conoid Geodesic Gridshell
Synclastic: Dome Geodesic Gridshell
Anticlastic: Saddle Geodesic Gridshell
#### On another note:

Alternate Gridshell Patterns [Source: IL 10 – Institute for Lightweight Structures and Conceptual Design]
Biosphere Environment Museum – Canada
Centre Pompidou-Metz – France
### 8.3 – Gridshell Construction

Hyperbolic Paraboloid: Straight Line Sweep Variation With Rotating Plank Line Grid
Hyperbolic Paraboloid: Flattened Plank Lines With Junctions
Toledo Gridshell 2.0. Construction Process [source: Timber gridshells – Numerical simulation, design and construction of a full scale structure]
# 9.0 Form Finding

### 9.0 – Minimal Surfaces

*Kangaroo2* Physics: Surface Tension Simulation
The Eden Project – United Kingdom
### 9.2 – Catenary Structures

*Kangaroo2* Physics: Catenary Model Simulation
### 9.3 – Biomimicry in Architecture

Example of Biomimicry
## Shapes, Fractals, Time &, the Dimensions they Belong to

### Foreword

# 1.0 Traditional Dimensions

Excerpt from ‘minutephysics’
### 1.1 – Zero Dimensions

###

### 1.2 – One Dimension

### 1.3 – Two Dimensions

### 1.4 – Three Dimensions

# 2.0 Fractal Dimensions

### 2.1 – Between the First & Second Dimensions

### 2.2 – Between the Second & Third Dimensions

Developing Koch Snowflake
Fourth Iteration Menger Sponge
### 2.3 – Calculating Fractal Dimensions

#### On another note:

# 3.0 Higher Dimensions

### 3.1 – The Fourth Dimension (Temporal)

Excerpt from ‘Seeker’
### 3.2 – The Fourth Dimension (Spacial)

3D representation of eight cubes folding in 4D space to form a Hypercube
### 3.3 – The Fifth and Sixth Dimensions

### 3.4 – Even Higher Dimensions

Cross section of the quintic Calabi–Yau manifold
## The Curves of Life

## Relevant Material

**Further Reading:**

*Biomimicry in Architecture by Michael Pawlyn*
## Adaptable Hypars

## Mesh Recursive Subdivision based on Alain Fournier’s algorithm

3Dimensional Greenhouse

Palm trees are angiosperms, which means flowering plants. They are monocots which means their seeds produce a single, leaf-like cotyledon when they sprout. This makes palms closely related to grasses and bamboo.

This mature palm shows how the pattern originally seen in the young plant, forms a distinct mathematic pattern known as ‘Phyllotaxis’. This is a pattern with reoccurs throughout nature and is based on the Fibonacci sequence. In order to try to understand the use and formation of the palm fibre, the overall formation of the palm stem needed to be mathematically explored.

However, redrawing the cross-section of the base of the palm plants allows a better understanding of the arrangement of the palm plant.

This exercise allows models to be made to recreate the patterns found in palm plants. By engineering plywood components, the basic shape of the palm geometry can be made into a physical model.

This was pushed further by curving the plywood components to make extruded palm structure models

The arrayed components can then be altered so that the base of the models form regular polygon shapes. Doing this allows the potential for the structures to be tesselated. Using different numbers of components mean the structure can then be tested for strength.

There are hundreds of used for palm fruits, this the plant producing materials which range from durable, to flexible to edible. One of the more interesting ones if the production of palm wine using the sap from the tree. Within 2 hours of the wine tapping process, the wine may reach up to 4%, by the following day the palm wine will become over fermented. Some prefer to drink the beverage at this point due to the higher alcohol content. The wine immediately begins fermenting, both from natural yeast in the air and from the remnants of wine left in the containers to add flavour. Ogogoro described a ‘local gin’, is a much stronger spirit made from Raffia palm tree sap. After extraction, the sap is boiled to form steam, which is then condensed and collected for consumption. Ogogoro is not synthetic ethanol but it is tapped from a natural source and then distilled.

To understand the fermentation process more clear, the process of fermenting sugar to make wine has been undertaken.

The distillation of the wine can be used to make bio-ethanol. This production of this fuel can act as a sustainable alternative to fossil fuel energy, which is overused and damaging to our environment.

The developed structure, as well as the production of palm wine and bio-ethanol, can be collaborated to develop a programme, which provides sustainable energy, within a space that is inviting and exciting.

The production of bio-fuel releases a lot of carbon dioxide. In order to ensure the process does not impact the environment, this needs to occur inside a closed system, so the CO2 does not enter the atmosphere. This can be done by using the properties of a Solar Updraft Tower. Carbon dioxide released from the fermentation and distillation processes can be received by palm trees for increased photosynthesis, while the excess oxygen from the trees provides fresh air for visitors.

The fermentation process can be controlled within an isolated area of the model.

The Distillation process, which requires a store of water for cooling, can also be conducted in an isolated area of the model, with apparatus incorporated into the structure.

The final proposal will be a combination of all three forms

The natural world is brimming with ratios, and spirals, that have been captivating mathematicians for centuries.

The term *phyllotaxis* (from the Greek *phullon* ‘**leaf**,’ and *taxis* ‘**arrangement**) was coined around the 17th century by a naturalist called Charles Bonnet. Many notable botanists have explored the subject, such as Leonardo da Vinci, Johannes Kepler, and the Schimper brothers. In essence, it is **the study of plant geometry** – the various strategies plants use to grow, and spread, their fruit, leaves, petals, seeds, etc.

Let’s say that you’re a flower. As a flower, you want to give each of your seeds the greatest chance of success. This typically means **giving them each as much room as possible to grow, and propagate**.

Starting from a given center point, **you have 360 degrees to choose from**. The first seed can go anywhere and becomes your reference point for ‘**0**‘ degrees. To give your seeds plenty of room, the next one is placed on the opposite side, all the way at **180°**. However the third seed comes back around another **180°**, and is now touching the first, which is a total disaster (for the sake of the argument, plants lack sentience in this instance: they can’t make case-by-case decisions and must stick to one angle (the technical term is a ‘*divergence angle*‘)).

Next time you only go to **90°** with your second seed, since you noticed free space on either side. This is great because you can place your third seed at **180°**, and still have room for another seed at **270°**. Bad news bears though, as you realise that all your subsequent seeds land in the same four locations. In fact, you quickly realise that any **number that divides 360° evenly yields exactly that many ‘spokes.’**

Note: This is technically true with numbers as high as 120, 180, or even 360(a spoke every 1°.) However the space between seeds in a spoke gradually becomes greater than the space between spokes themselves, leaving you with one big spiral instead.

These ‘spokes’ are the result of the periodic nature of a circle. When defining an angle for this experiment, the more ‘*ratio*nal’ it is, the poorer the spread will be (**a number is rational if it can be expressed as the ratio of two integers**). Naturally this implies that a number can be irrational.

Sal Khan has a great series of short videos going over the difference between the two [Link]. For our purposes, the important take-aways are:

-Between any two rational numbers, there is at least on irrational number.

–**Irrational numbers go on and on forever**, and never repeat.

You go back to being a flower.

Since you’ve just learned that **an angle defined by a rational number gives you a lousy distribution**, you decide to see what happens when you use an angle defined by an irrational number. Luckily for you, some of the most famous numbers in mathematics are irrational, like **π** (pi), **√2** (Pythagoras’ constant), and **e** (Euler’s number). Dividing your circle by **π** (360°/3.14159…) leaves you with an angle of roughly **114.592°**. Doing the same with **√2** and **e** leave you with **254.558°** and **132.437°** respectively.

Great success. These angles are already doing a much better job of dispersing your seeds. It’s quite clear to you that **√2** is doing a much better job than **π**, however the difference between **√2** and **e** appears far more subtle. Perhaps expanding these sequences will accentuate the differences between them.

It’s not blatantly obvious, but **√2** appears to be producing a slightly better spread. The next question you might ask yourself is then: is it possible to measure the difference between the them? How can you prove which one really is the best? What about Theodorus’, Bernstein’s, or Sierpiński’s constants? There are in fact an infinite amount of mathematical constants to choose from, most of which do not even have names.

Numbers can either be rational or irrational. However **some irrational numbers are actually more irrational than others**. For example, **π** is technically irrational (it does go on and on forever), but it’s not exceptionally irrational. This is because it’s approximated quite well with fractions – it’s pretty close to 3+1⁄7 or 22⁄7. It’s also why if you look at the phyllotaxis pattern of **π**, you’ll find that there are 3 spirals that morph into 22 (I have no idea how or why this is. It’s pretty rad though).

Generating a voronoi diagram with your phyllotaxis patterns is a pretty neat way of indicating exactly how much real estate each of your seeds is getting. Furthermore, you can **colour code each cell based on proximity to nearest seed**. In this case, purple means the nearest neighbour is quite close by, and orange/red means the closet neighbour is relatively far away.

Congratulations! You can now empirically prove that *√2* is in fact more effective than **e** at spreading seeds (**e**‘s spread has more purple, blue, and cyan, as well as less yellow (meaning more seeds have less space)). But this begs the question: how then, can you find the most irrational number? Is there even such a thing?

You could just check **every single angle between 0° and 360°** to see what happens.

This first thing you (by which ‘you,’ I mean ‘I’) notice is: holy cats, that’s a lot of options to choose from; how the hell are you suppose to know where to start?

The second thing you notice is **that the pattern is actually oscillating between spokes and spirals**, which makes total sense! What you’re effectively seeing is every possible **rational** angle (in order), while hitting the **irrational** one in between. Unfortunately you’re still not closer to picking the most irrational one, and there are far too many to compare one by one.

Fortunately you don’t have to lose any sleep over this, because there is actually a number that has been mathematically proven to be **the most irrational of all**. This number is called **phi** (a.k.a. the Golden/Divine + Ratio/Mean/Proportion/Number/Section/Cut etc.), and is commonly written as **Φ** (uppercase), or **φ** (lowercase).

It is the most irrational number because it is **the hardest to approximate with fractions**. Any number can be represented in the form of something called a continued fraction. Rational numbers have finite continued fractions, whereas irrational numbers have ones that go on forever. You’ve already learned that **π** is not very irrational, as it’s value is approximated pretty well quite early on in its continued fraction (even if it does keep going forever). On the other hand, you can go far further in **Φ**‘s continued fraction and still be quite far from its true value.

*Source:*

*Infinite fractions and the most irrational number: [Link]*

*The Golden Ratio (why it is so irrational): [Link]*

Since you’re (by which ‘you’re,’ I mean I’m) a flower (by which ‘a flower,’ I mean ‘an architecture student’), and not a number theorist, it’s less important to you why it’s so irrational, and more so just that it is so. So then, you plot your seeds using **Φ**, which gives you an angle of roughly **137.5°**.

It seems to you that this angle does a an excellent job of distributing seeds evenly. **Seeds always seem to pop up in spaces left behind by old ones, while still leaving space for new ones**.

Expanding the this pattern, as well as the generation of a voronoi diagram, further supports your observations. You could compare **Φ**‘s colour coded voronoi/proximity diagram with the one produced using **√2**, or any other irrational number. What you’d find is that *Φ* does do the better job of evenly spreading seeds. However **√2 **(among with many other irrational numbers) is still pretty good.

If you were to plot a range of angles, along with their respective voronoi/proximity diagrams, you can see there are plenty of irrational numbers that are comparable to **Φ** (even if the range is tiny). The following video plots a range of only **1.8°**, but sees six decent candidates. If the remaining **358.2°** are anything like this, then there could easily well **over ten thousand irrational numbers** to choose from.

It’s worth noting that this is technically not how plants grow. Rather than being added to the outside, **new seeds grow from the middle and push everything else outwards**. This also happens to by why **phyllotaxis is a radial expansion** by nature. In many cases the same is true for the growth of leaves, petals, and more.

It’s often falsely claimed that the **Φ** shows up everywhere in nature. Yes, it can be found in lots of plants, and other facets of nature, but not as much as some people mi

ght have you believe. You’ve seen that **there are countless irrational numbers that can define the growth of a plant in the form of spirals**. What you might not know is that there is such as thing as the *Silver Ratio*, as well as the *Bronze Ratio*. The truth is that there’s actually **a vast variety of logarithmic spirals** that can be observed in nature.

*Source:*

*The Silver Ratio & Metallic Means: [Link]*

A huge variety of plants have been observed to exhibit spirals in their growth (~80% of the 250,000+ different species (some plants even grow leaves at 90° and 180° increments)). **These patterns facilitate photosynthesis, give leaves maximum exposure to sunlight and rain, help moisture spiral efficiently towards roots, and or maximize exposure for insect pollination**. These are just a few of the ways plants benefit from spiral geometry.

Some of these patterns may be **physical phenomenons**, defined by their surroundings, as well as various **rules of growth**. They may also be results of natural selection – of long series of **genetic deviations** that have stood the test of time. For most cases, the answer is likely a combination of these two things.

In some of the cases, you could make an compelling arrangement suggesting that these spirals don’t even exist. This quickly becomes a pretty deep philosophical question. If you put a series of points in a row, one by one, when does it become a line? How close do they have to be? How many do you have to have? The answer is kinda slippery, and subjective. A line is mathematically defined by an infinite sum of points, but the brain is pretty good at seeing patterns (even ones that don’t exist).

M.C. Escher said that *we adore chaos because we love to produce order.* Alain Badiou also said that

Grids, shells, and how they, in conjunction with the study of the natural world, can help us develop increasingly complex structural geometry.

This post is **the third installment of sort of trilogy**, after *Shapes, Fractals, Time & the Dimensions they Belong to*, and *Developing Space-Filling Fractals*. While it’s not important to have read either of those posts to follow this one, I do think it adds a certain level of depth and continuity.

Regarding my previous entries, it can be difficult to see how any of this has to do with architecture. In fact I know a few people who think studying fractals is pointless.

Admittedly I often struggle to explain to people what fractals are, let alone how they can influence the way buildings look. However, I believe that this post really sheds light on how **these kinds of studies may directly** **influence and enhance our understanding **(and perhaps even the future)** of our built environment**.

On a separate note, I heard that a member of the architectural academia said “forget biomimicry, it doesn’t work.”

Firstly, I’m pretty sure Frei Otto would be rolling over in his grave.

Secondly, if someone thinks that biomimicry is useless, it’s because they don’t really understand what biomimicry is. And I think the same can be said regarding the study of fractals. They are closely related fields of study, and I wholeheartedly believe they are **fertile grounds for architectural marvels to come**.

As far as classification goes, shells generally fall under the category of **two-dimensional shapes**. They are defined by a curved surface, where the material is thin in the direction perpendicular to the surface. However, assigning a dimension to certain shells can be tricky, since it kinda depends on how zoomed in you are.

A strainer is a good example of this – a two-dimensional gridshell. But if you zoom in, it is comprised of a series of woven, one-dimensional wires. And if you zoom in even further, you see that each wire is of course comprised of a certain volume of metal.

This is a property shared with many fractals, where **their dimension can appear different depending on the level of magnification**. And while there’s an infinite variety of possible shells, they are (for the most part) categorizable.

Analytic geometry is created in relation to Cartesian planes, using mathematical equations and a coordinate systems. Synthetic geometry is essentially free-form geometry (that isn’t defined by coordinates or equations), with the use of a variety of curves called *splines*. The following shapes were created via Synthetic geometry, where we’re calling our splines ‘*u’* and ‘*v*.’

These curves highlight each dimension of the two-dimensional surface. In this case only one of the two ‘curves’ is actually curved, making this shape **developable**. This means that if, for example, it was made of paper, **you could flatten it** completely.

Uniclastic: Conoid (Conical paraboloid)

In this case, one of them grows in length, but the other still remains straight. Since one of the dimensions remains straight, it’s still a single curved surface – **capable of being flattened** without changing the area. Singly curved surfaced may also be referred to as *uniclastic* or *monoclastic*.

These can be classified as *synclastic* or *anticlastic*, and are **non-developable** surfaces. If made of paper, **you could not flatten them** without tearing, folding or crumpling them.

In this case, both curves happen to be identical, but what’s important is that **both dimensions are curving in the same direction**. In this orientation, the dome is also under compression everywhere.

The surface of the earth is double curved, synclastic – non-developable. “The surface of a sphere cannot be represented on a plane without distortion,” a topic explored by Michael Stevens: https://www.youtube.com/watch?v=2lR7s1Y6Zig

This one was formed by non-uniformly sweeping a **convex parabola along a concave parabola**. It’s internal structure will behave differently, depending on the curvature of the shell relative to the shape. Roof shells have compressive stresses along the convex curvature, and tensile stress along the concave curvature.

Here is an example of a beautiful marriage of **tensile and compressive** potato and wheat-based anticlastic forces. Although I hear that Pringle cans are diabolically heinous to recycle, so they are the enemy.

In terms of synthetic geometry, there’s more than one approach to generating anticlastic curvature:

This shape was achieved by sweeping a straight line over a straight path at one end, and another straight path at the other. This will work as long as both rails are not parallel. Although I find this shape perplexing; it’s double curvature that you can create with straight lines, yet non-developable, and I can’t explain it..

The ruled surface was created by sliding a plane curve (a straight line) along another plane curve (a circle), while keeping the angle between them constant. The surfaces of revolution was simply made by revolving a plane curve around an axis. (Surface of translation also exist, and are similar to ruled surfaces, only the orientation of the curves is kept constant instead of the angle.)

The hyperboloid has been a popular design choice for (especially nuclear cooling) towers. It has **excellent tensile and compressive properties**, and **can be built with straight members**. This makes it relatively cheap and easy to fabricate relative to it’s size and performance.

These towers are pretty cool acoustically as well: https://youtu.be/GXpItQpOISU?t=40s

These are singly curved curves, although that does sound confusing. A simple way to understand what geodesic curves are, is to give them a width. As previously explored, we know that curves can inhabit, and fill, two-dimensional space. However, you can’t really observe the twists and turns of **a shape that has no thickness**.

A ribbon is essentially a straight line with thickness, and when used to follow the curvature of a surface (as seen above), the result is a plank line. The term ‘plank line’ can be defined as a line with an given width (like a plank of wood) that passes over a surface and **does not curve in the tangential plane,** and whose width is always tangential to the surface.

Since one-dimensional curves do have an orientation in digital modeling, geodesic curves can be described as the one-dimensional counterpart to plank lines, and can benefit from the same definition.

The University of Southern California published a paper exploring the topic further: http://papers.cumincad.org/data/works/att/f197.content.pdf

For simplicity, here’s a basic grid set up on a flat plane:

We start by defining two points anywhere along the edge of the surface. Then we find the geodesic curve that joins the pair. Of course it’s trivial in this case, since we’re dealing with a flat surface, but bear with me.

We can keep adding pairs of points along the edge. In this case they’re kept evenly spaced and uncrossing for the sake of a cleaner grid.

After that, it’s simply a matter of playing with density, as well as adding an additional set of antagonistic curves. For practicality, each set share the same set of base points.

He’s an example of a grid where each set has their own set of anchors. While this does show the flexibility of a grid, I think it’s far more advantageous for them to share the same base points.

The same principle is then applied to a series of surfaces with varied types of curvature.

First comes the shell (a barrel vault in this case), then comes the grid. The symmetrical nature of this surface translates to a pretty regular (and also symmetrical) gridshell. The use of geodesic curves means that these **gridshells can be fabricated using completely straight material**, that only necessitate single curvature.

The same grid used on a conical surface starts to reveal gradual shifts in the geometry’s spacing. **The curves always search for the path of least resistance** in terms of bending.

This case illustrates the nature of geodesic curves quite well. The dome was free-formed with a relatively high degree of curvature. A small change in the location of each anchor point translates to a large change in curvature between them. Each curve looks for **the shortest path between each pair** (without leaving the surface), but only has access to single curvature.

Structurally speaking, things get much more interesting with anticlastic curvature. As previously stated, each member will behave differently based on their relative curvature and orientation in relation to the surface. Depending on their location on a gridshell, **plank lines can act partly in compression and partly in tension**.

While geodesic curves make it far more practical to fabricate shells, they are not a strict requirement. Using non-geodesic curves just means more time, money, and effort must go into the fabrication of each component. Furthermore, there’s no reason why you can’t use alternate grid patterns. In fact, **you could use any pattern under the sun** – any motif your heart desires (even tessellated puppies.)

Here are just a few of the endless possible pattern. They all have their advantages and disadvantages in terms of fabrication, as well as structural potential.

Gridshells with large amounts of triangulation, such as Buckminster Fuller’s geodesic spheres, typically perform incredibly well structurally. These structure are also highly efficient to manufacture, as their geometry is extremely repetitive.

Gridshells with highly irregular geometry are far more challenging to fabricate. In this case, each and every piece had to be custom made to shape; I imagine it must have costed a lot of money, and been a logistical nightmare. Although it is an exceptionally stunning piece of architecture (and a magnificent feat of engineering.)

In our case, building these shells is simply a matter of converting the geodesic curves into **planks lines**.

The whole point of using them in the first place is so that we can make them out of straight material that don’t necessitate double curvature. This example is rotating so the shape is easier to understand. It’s grid is also rotating to demonstrate the ease at which you can play with the geometry.

This is what you get by taking those plank lines and laying them flat. In this case both sets are the same because the shell happens to the identicall when flipped. Being able to use straight material means far less labour and waste, which translates to faster, and or cheaper, fabrication.

**An especially crucial aspect of gridshells is the bracing**. Without support in the form of tension ties, cable ties, ring beams, anchors etc., many of these shells can lay flat. This in and of itself is pretty interesting and does lends itself to unique construction challenges and opportunities. This isn’t always the case though, since sometimes it’s the geometry of the joints holding the shape together (like the geodesic spheres.) Sometimes the member are pre-bent (like Pompidou-Metz.) Although pre-bending the timber kinda strikes me as cheating thought.. As if it’s not a genuine, bona fide gridshell.

This is one of the original build method, where the gridshell is assembled flat, lifted into shape, then locked into place.

Having studied the basics makes exploring increasingly elaborate geometry more intuitive. In principal, most of the shells we’ve looked are known to perform well structurally, but there are strategies we can use to focus specifically on **performance optimization**.

These are surfaces that are locally area-minimizing – surfaces that have **the smallest possible area for a defined boundary**. They necessarily have zero mean curvature, i.e. the sum of the principal curvatures at each point is zero. Soap bubbles are a great example of this phenomenon.

Hyperbolic Paraboloid Soap Bubble [Source: Serfio Musmeci’s “Froms With No Name” and “Anti-Polyhedrons”]Soap film inherently forms shapes with the least amount of area needed to occupy space – that minimize the amount of material needed to create an enclosure. Surface tension has physical properties that naturally relax the surface’s curvature.

We can simulate surface tension by using a network of curves derived from a given shape. Applying varies material properties to the mesh results in a shape that can behaves like stretchy fabric or soap. **Reducing the rest length of each of these curves** (while keeping the edges anchored) makes them pull on all of their neighbours, resulting in a locally minimal surface.

Here are a few more examples of minimal surfaces you can generate using different frames (although I’d like stress that the possibilities are extremely infinite.) The first and last iterations may or may not count, depending on which of the **many definitions of minimal surfaces** you use, since they deal with pressure. You can read about it in much greater detail here: https://tinyurl.com/ya4jfqb2

Here we have one of the most popular examples of minimal surface geometry in architecture. The shapes of these domes were derived from a series of studies using clustered soap bubbles. The result is a series of enormous shells built with an impressively small amount of material.

Triply periodic minimal surfaces are also a pretty cool thing (surfaces that have a crystalline structure – that tessellate in three dimensions):

Another powerful method of form finding has been **to let gravity dictate the shapes of structures**. In physics and geometry, catenary (derived from the Latin word for chain) curves are found by letting a chain, rope or cable, that has been anchored at both end, hang under its own weight. They look similar to parabolic curves, but perform differently.

A net shown here in magenta has been anchored by the corners, then draped under simulated gravity. This creates a network of hanging curves that, when converted into a surface, and mirrored, ultimately forms a catenary shell. This geometry can be used to generate a gridshell that **performs exceptionally well under compression**, as long as the edges are reinforced and the corners are braced.

While I would be remiss to not mention Antoni Gaudí on the subject of catenary structure, his work doesn’t particularly fall under the category of gridshells. Instead I will proceed to gawk over some of the stunning work by Frei Otto.

Of course his work explored a great deal more than just catenary structures, but he is revered for his beautiful work on gridshells. He, along with the Institute for Lightweight Structures, have truly been pioneers on the front of theoretical structural engineering.

There are a few different terms that refer to this practice, including biomimetics, bionomics or bionics. In principle they are all more or less the same thing; **the practical application of discoveries derived from the study of the natural world** (i.e. anything that was not caused or made by humans.) In a way, this is the fundamental essence of the scientific method: to learn by observation.

Frei Otto is a fine example of ecological literacy at its finest. **A profound curiosity of the natural world greatly informed his understanding of structural technology**. This was all nourished by countless inquisitive and playful investigations into the realm of physics and biology. He even wrote a series of books on the way that the morphology of bird skulls and spiderwebs could be applied to architecture called Biology and Building. His ‘IL‘ series also highlights a deep admiration of the natural world.

Of course he’s the not the only architect renown their fascination of the universe and its secrets; Buckminster Fuller and Antoni Gaudí were also strong proponents of biomimicry, although they probably didn’t use the term (nor is the term important.)

Gaudí’s studies of nature translated into his use of ruled geometrical forms such as hyperbolic paraboloids, hyperboloids, helicoids etc. He suggested that there is no better structure than the trunk of a tree, or a human skeleton. **Forms in biology tend to be both exceedingly practical and exceptionally beautiful**, and Gaudí spent much of his life discovering how to adapt the language of nature to the structural forms of architecture.

Fractals were also an undisputed recurring theme in his work. This is especially apparent in his most renown piece of work, the *Sagrada Familia*. **The varying complexity of geometry, as well as the particular richness of detail, at different scales is a property uniquely shared with fractal nature.**

Antoni Gaudí and his legacy are unquestionably one of a kind, but I don’t think this is a coincidence. I believe the reality is that **it is exceptionally difficult to peruse biomimicry, and especially fractal geometry, in a meaningful way in relation to architecture**. For this reason there is an abundance of superficial appropriation of organic, and mathematical, structures without a fundamental understanding of their function. At its very worst, an architect’s approach comes down to: ‘I’ll say I got the structure from an animal. Everyone will buy one because of the romance of it.”

That being said, modern day engineers and architects continue to push this envelope, granted with varying levels of success. Although I believe that **there is a certain level of inevitability when it comes to how architecture is influenced by natural forms**. It has been said that, the more efficient structures and systems become, the more they resemble ones found in nature.

Euclid, the father of geometry, believed that nature itself was the physical manifestation of mathematical law. While this may seems like quite a striking statement, what is significant about it is **the relationship between mathematics and the natural world**. I like to think that this statement speaks less about the nature of the world and more about the nature of mathematics – that math is our way of expressing how the universe operates, or at least our attempt to do so. After all, Carl Sagan famously suggested that, in the event of extra terrestrial contact, we might use various universal principles and facts of mathematics and science to communicate.

First, second and third dimensions, and why fractals don’t belong to any of them, as well as what happens when you get into higher dimensions.

In this post, I’m going to try my best to explain the **first, second, and third dimensions**, and why **fractals** don’t belong to any of them, as well as what happens when you get into **higher dimensions**. But before getting into the nitty-gritty of the subject, I think it’s worth prefacing this post with a short note on the nature of mathematics itself:

Alain Badiou said that mathematics is a** rigorous aesthetic**; it tells us nothing of real being, but forges a **fiction of intelligible consistency**. That being said, I think it’s interesting to think about whether or not mathematics were invented or discovered – whether or not numbers exist outside of the human mind.

While I don’t have an answer to this question (and there are at least three different schools of thought on the subject), I do think it’s important to keep in mind that we only use math as **a tool **to measure and represent ‘real world’ things. In other words, our knowledge of **mathematics has its limitations** as far as understanding the space-time continuum goes.

In physics and mathematics, dimensions are used to define the Cartesian plains. The measure of a mathematical space is based on the **number of variables require** to define it. The dimension of an object is defined by **how many coordinates are required** to specify a point on it.

It’s important to note that there is no ‘first’ or ‘second’ dimension. It’s a bit like pouring three cups of water into a vase and asking someone which cup is the first one. The question doesn’t even make sense.

We usually arbitrarily pick a dimension and calling it the ‘first’ one.

Something of zero dimensions give us **a point**. While a point can inhabit (and be defined in) higher dimensions, the point itself has a dimension of zero; you cannot move anywhere on a point.

A line or a curve gives us a one-dimensional object, and is **typically bound by two zero-dimensional things**.

Only **one coordinate** is required to define a point on the curve.

Similarly to the point, a curve can inhabit higher dimension (i.e. you can plot a curve in three dimensions), but as an object, it only possesses one dimension.

Another way to think about it is: if you were to walk along this curve, you could only go forwards or backward – **you’d only have access to one dimension**, even though you’d be technically moving through three dimensions.

Surfaces or plains gives us two-dimensional shapes, and are** typically bound by one-dimensional shapes **(lines/curves).

A plain can be defined by ** x**&

A surface can live in three+ dimensions, but still only possesses two dimension. **Two coordinate** are required to define a point on a surface. For example a sphere is a three-dimensional object, but the surface of a sphere is two-dimensional – a point can be defined on the surface of a sphere with latitude and longitude.

A volume gives us a three-dimensional shape, and **can be bound by two-dimensional shapes **(surfaces).

Shapes in three dimensions are most commonly represented in relation to an **x**, **y** and **z** axis. If a person were to swim in a body of water, their position could be defined by no less than **three coordinates** – their latitude, longitude and depth. Traveling through this body of water grants access to three dimensions.

Fractals can be generally classified as **shapes with a non-integer dimension **(a dimension** **that is not a whole number). They may or may not be self-similar, but are typically measured by their properties at different scales.

Felix Hausdorff and Abram Besicovitch demonstrated that, though a line has a dimension of one and a square a dimension of two, **many curves fit in-between dimensions** due to the varying amounts of information they contain. These **dimensions between whole numbers **are known as Hausdorff-Besicovitch dimensions.

A line or a curve gives us a one-dimensional object that allows us to move forwards and backwards, where only **one coordinate** is required to define a point on them.

Surfaces give us two-dimensional shapes, where **two coordinate** are required to define a point on them.

Here is a shape that cannot be classified as a one-dimensional shape, or a two-dimensional shape. It can be plotted in two dimensions, or even three dimensions, but the object itself **does not have access the two whole dimensions**.

If you were to walk along the shape starting from the base, you could go forwards and backwards, but suddenly you have an option that’s more than forwards and backwards, but less than left and right.

You cannot define a point on this shape with a single coordinate, and a two coordinate system would define a point off of the shape more often than not.

Each fractal has a unique dimensional measure based on how much space they fill.

The same logic applies when exploring fractals plotted in three dimensions:

**two coordinate** are required to define a point on them.

A volume gives us a three-dimensional shape where a point could be defined by no less than **three coordinates**.

While these models live in three dimensions, they do not quite have access to all of them. You cannot define a point on them with two coordinates: they are **more than a surface and less than a volume**.

The Menger Sponge for example has (mathematically) a volume of zero, but an infinite surface area.

The following are three methods of calculating Hausdorff-Besicovitch dimension:

• The exactly self-similar method for calculating dimensions of mathematically generated repeating patterns.

• The Richardson method for calculating a dimensional slope.

• The box-counting method for determining the ratios of a fractal’s area or volume.

In theory, higher (non-integer) dimensional fractals are possible.

As far as I’m concerned however, they’re not particularly good for anything in a three-dimensional world. You are more than welcome to prove me wrong though.

Sadly, living in a three-dimensional world makes it especially difficult to think about, and **nearly impossible to visualise, higher dimensions**. This is in the same way that a two-dimensional being would find it impossibly hard to think about our three-dimensional world, a subject explored in the novel ‘*Flatland’* by Edwin A. Abbott.

That being said, it’s plausible that we experience much higher dimensions that are just **too hard to perceive**. For example, an ant walking along the surface of a sphere will only ever perceive two dimensions, but is moving through three dimensions, and is subject to the fourth (temporal) dimension.

If we consider time an additional variable, then despite the fact that we live in a three dimensional world, we are always subject to (even if we cannot visualize) a fourth dimension.

Neil deGrasse Tyson puts it quite plainly by saying:

“[…]** you have never met someone at a place, unless it was at a time; you have never met someone at a time, unless it was at a place **[…]”

Suppose we call our first three dimensions *x*, *y* & **z**, and our fourth** t**:** **latitude, longitude, altitude and time, respectively. In this instance, **time is linear**, and time & space are one. As if the universe is a kind of film, where going forwards and backwards in time will always yield the exact same outcome; no matter how many times you return to a point in point time, you will always find yourself (and everything else) in the exact same place.

However time is only linear for us as three-dimensional beings. For a four-dimensional being, **time is something that can be moved through as freely** as swimming or walking.

If we explore **spacial dimensions**, a four-dimensional object may be achieved by ‘folding’ three-dimensional objects together. They cannot exist in our three-dimensional world, but there are tricks to visualise them.

We know that we can construct a cube by folding a series of two-dimensional surfaces together, but this is only possible with the third dimension, which we have access to.

If we visualise, in two dimensions, a cube rotating (as seen above), it looks like each surface is distorting, growing and shrinking, and is passing through the other. However we are familiar enough with the cube as a shape to know that this is simply **a trick of perspective** – that objects only* look* smaller when they are farther away.

In the same way that a cube is made of six squares, a four-dimensional cube (hypercube or tesseract), is made of eight cubes.

- A line is bound by two zero-dimensional things
- A square is bound by four one-dimensional shapes
- A cube is bound by six two-dimensional surfaces
- A hypercube, bound by eight three-dimensional volumes

It looks like each cube is distorting, growing and shrinking, and passing through the other. This is because **we can only represent eight cubes folding together** in the fourth dimension with three-dimensional perspective animation.

Perspective makes it *look* like the cubes are growing and shrinking, when** they are simply getting closer and further in four-dimensional space**. If somehow we could access this higher dimension, we would see these cubes fold together unharmed the same way forming a cube leaves each square unharmed.

Below is a three-dimensional perspective view of hypercube rotating in four dimensions, where (in four-dimensional space) all eight cubes are always the same, but are being subjected to perspective.

On the temporal side of things, adding the ability to move ‘left & right’ and ‘up & down’ in time gives us the fifth and sixth dimensions.

(For example: ** x, y, z, t_{1}, t_{2}, t_{3}**)

This is a space where one can move through time based on probability and permutations of what could have been, is, was, or will be on **alternate timelines**. For any one point in this space, there are **six coordinates** that describe its position.

In spacial dimensions, it is theoretically possible to fold four-dimensional objects with a fifth dimension. However, **it becomes increasingly difficult for us to visualise** what is happening to the shapes that we’re folding.

In theory, objects can keep being folded together into higher and higher spacial dimensions indefinitely. (*R*_{1}, R_{2}, R_{3},R_{4},R_{5}, R_{6}, R_{7 }etc.)

There’s a terrific explanation of what happens to platonic solids and regular polytopes in higher dimensions on Numberphile: https://youtu.be/2s4TqVAbfz4

If we can take a point and move it through space and time, including all the futures and pasts possible, for that point, we can then move along a number line where **the laws of gravity are different, the speed of light has changed**.

Dimensions seven though ten are **different universes** with different possibilities, and impossibilities, and even different laws of physics. These grasp all the possibilities and permutations of how each universe operates, and the whole of reality with all the permutations they’re in, throughout all of time and space. The highest dimension is the encompassment of all of those universes, possibilities, choices, times, places all into a single ‘thing.’

These ten time-space dimensions belong to something called **Super-string Theory**, which is what physicists are using to help us understand how the universe works.

There may very well be a link between temporal dimensions and spacial dimensions. For all I know, they are actually the same thing, but thinking about it for too long makes my head hurt. If the topic interests you, there is a philosophical approach to the nature of time called ‘*eternalism’*, where one may find answers to these questions. Other dimensional models include M-Theory, which suggests there are eleven dimensions.

While we don’t have experimental or observational evidence to confirm whether or not any of these additional dimensions really exist, theoretical physicists continue to use these studies to help us learn more about how the universe works. Like how gravity affects time, or the higher dimensions affect quantum theory.

“An organism is so complex a thing, and growth so complex a phenomenon, that for growth to be so uniform and constant in all the parts as to keep the whole shape unchanged would indeed be an unlikely and an unusual circumstance. Rates vary, proportions change, and the whole configuration alters accordingly.” – D’Arcy Wentworth Thompson

*“This is the classic reference on how the golden ratio applies to spirals and helices in nature.” – Martin Gardner*

What makes this book particularly enjoyable to flip through is an abundance of beautiful hand drawings and diagrams. Sir Theodore Andrea Cook explores, in great detail, the nature of spirals in the structure of plants, animals, physiology, the periodic table, galaxies etc. – from tusks, to rare seashells, to exquisite architecture.

He writes, “*a staircase whose form and construction so vividly recalled a natural growth would, it appeared to me, be more probably the work of a man to whom biology and architecture were equally familiar than that of a builder of less wide attainments. It would, in fact, be likely that the design had come from some great artist and architect who had studied Nature for the sake of his art, and had deeply investigated the secrets of the one in order to employ them as the principles of the other.*”

Cook especially believes in a hands-on approach, as oppose to mathematic nation or scientific nomenclature – seeing and drawing curves is far more revealing than formulas.

“*because I believe very strongly that if a man can make a thing and see what he has made, he will understand it much better than if he read a score of books about it or studied a hundred diagrams and formulae. And I have pursued this method here, in defiance of all modern mathematical technicalities, because my main object is not mathematics, but the growth of natural objects and the beauty (either in Nature or in art) which is inherent in vitality.*”

Despite this, it is clear that Theodore Cook has a deep love of mathematics. He describes it at the beautifully precise instrument that allows humans to satisfy their need to catalog, label and define the innumerable facts of life. This ultimately leads him into profoundly fascinating investigations into the geometry of the natural world.

*“An organism is so complex a thing, and growth so complex a phenomenon, that for growth to be so uniform and constant in all the parts as to keep the whole shape unchanged would indeed be an unlikely and an unusual circumstance. Rates vary, proportions change, and the whole configuration alters accordingly.” **– D’Arcy Wentworth Thompson*

D’Arcy Wentworth Thompson wrote, on an extensive level, why living things and physical phenomena take the form that they do. By analysing mathematical and physical aspects of biological processes, he expresses correlations between biological forms and mechanical phenomena.

He puts emphasis on the roles of physical laws and mechanics as the fundamental determinants of form and structure of living organisms. D’Arcy describes how certain patterns of growth conform to the golden ratio, the Fibonacci sequence, as well as mathematics principles described by Vitruvius, Da Vinci, Dürer, Plato, Pythagoras, Archimedes, and more.

While his work does not reject natural selection, it holds ‘survival of the fittest’ as secondary to the origin of biological form. The shape of any structure is, to a large degree, imposed by what materials are used, and how. A simple analogy would be looking at it in terms of architects and engineers. They cannot create any shape building they want, they are confined by physical limits of the properties of the materials they use. The same is true to any living organism; the limits of what is possible are set by the laws of physics, and there can be no exception.

*“You could look at nature as being like a catalogue of products, and all of those have benefited from a 3.8 billion year research and development period. And given that level of investment, it makes sense to use it.” – Michael Pawlyn*

Michael Pawlyn, one of the leading advocates of biomimicry, describes nature as being a kind of source-book that will help facilitate our transition from the industrial age to the ecological age of mankind. He distinguishes three major aspects of the built environment that benefit from studying biological organisms:

The first being the quantity on resources that use, the second being the type of energy we consume and the third being how effectively we are using the energy that we are consuming.

Exemplary use of materials could often be seen in plants, as they use a minimal amount of material to create relatively large structures with high surface to material ratios. As observed by Julian Vincent, a professor in Biomimetics, “materials are expensive and shape is cheap” as opposed to technology where the inverse is often true.

Plants, and other organisms, are well know to use double curves, ribs, folding, vaulting, inflation, as well as a plethora of other techniques to create forms that demonstrate incredible efficiency.

An exploration of the simplest Hyperbolic Paraboloidic ‘saddle’ form has lead to the development of a modular system that combines the principles of the hypar (Hyperbolic Paraboloid) and elastic potential energy.

A hyperbolic paraboloid is an infinite doubly ruled surface in three dimensions with hyperbolic and parabolic cross-sections. It can be parametrized using the following equations:

Mathematical: z = x^{2} – y^{2 }or x = y z

Parametric: x(u,v)=u y(u,v)=v z(u,v)=uv

The physical manifestation of the above equations can be achieved by constructing a square and forcing the surface area to minimalise by introducing cross bracing that has shorter lengths than the square edges.

A particular square hypar defined by b = n * √2 (b=boundary, n=initial geometry or ‘cross bracing’) thus constricting the four points to the corners of a cube leads to interesting tessellations in three dimensions.

Using a simple elastic lashing system to construct a hypar module binds all intersections together whilst allowing rotational movement. The rotational movement at any given intersection is proportionally distributed to all others. This combined with the elasticity of the joints means that the module has elastic potential energy (spring-like properties) therefore an array of many modules can adopt the same elastic properties.

The system can be scaled, shaped, locked and adapted to suit programmatic requirements.

The principle of the subdivision method to generate mountains is to recursively subdivide (split) polygons of a model up to a required level of detail. At the same time the parts of the split polygons will be perturbed. The initial shape of the model is retained to an extent, depending on the perturbations. Thus, a central point of the fractal subdivision algorithm is perturbation as a function of the subdivision level.

Concerning mountains, the higher the level the smaller the perturbation, otherwise the mountains would get higher and higher. In addition there must be a random number generator to obtain irregularities within the shape – and to achieve a kind of statistical similarity:

P_n = p( n ) * rnd();

Where p_n = perturbation at level n,

P( ) = perturbation function depending on level n, and

Rnd( ) = random number generator.

Fournier developed a subdivision algorithm for a triangle. Here, the midpoints of each side of the triangle are connected, creating four new sub triangles.

**Based on this algorithm, the process is done recursively to all the new triangles generated so that the shape is not limited to vertical mountains.**

Random perturbation is where the first iteration is based on a random parameter within the range of 0-9 and the following iterations also are based on a random parameter. This is done using grasshopper by setting the seed number of the initial polygon and the seed number of the iterations. All iterations perturbed based on the z-axis of the new polygon produced.

This resulted in a different shape of the ‘base’ and all the iterations after the first one, ranging from small to big volume depending on the seed of the random number generated. By producing polygons using random perturbation, each iteration is different than the others. The iteration runs for ten (10) times using grasshopper.

Base perturbation * random seed: 1 – 10

Second – third perturbation * random seed: 0 – 10

Based on the principle, one module is chose to continue with the next step. The module chosen is the 5;5 module which is **Base perturbation * random seed: 5** and **Second – third perturbation * random seed: 5**. After the second iteration, whenever there are surfaces which will intersect, one or both of the surface is removed. This resulted in a random yet in control structure based on the principle applied.

For the next brief, I am developing the module to grow further than the third iteration and grows following a certain flow.